Spectrum-Effect Relationship Analysis of Bioactive Compounds in Zanthoxylum nitidum (Roxb.) DC. by Ultra-High Performance Liquid Chromatography Mass Spectrometry Coupled With Comprehensive Filtering Approaches

An algorithm-driven intelligent mining and identification strategy for natural product mass spectrometry

Efficiently mining and identification of new compounds from the extensive MS/MS datasets of plant extracts poses a significant challenge due to the structural diversity and compositional complexity inherent in natural products (NPs). Various data post-processing techniques have been developed to simplify the interpretation of MS/MS data; however, they often suffer from limited specificity and precision. Meanwhile, structure annotation following data post-processing is particularly time-consuming. In this study, we introduced an innovative strategy named MS-SMART, which integrates three intelligent algorithms: automatic mining of diagnostic ions, rapid filtration of alkaloids from untargeted MS/MS data, and structural recommendations for filtered components. The feasibility of this approach for rapidly discovering novel compounds was demonstrated using berberine-type alkaloids as an example. Firstly, diagnostic ions were automatically extracted and validated using available reference data. Subsequently, berberine-type compounds were filtered from raw MS/MS data. Finally, the structures of the target components were recommended using building blocks derived from berberines reported in various plants. A total of 103, 198, 60, 80 and 51 berberines were efficiently identified in diverse families and genera, including Stephaniae Epigaeae Radix, Coptidis Rhizoma, Phellodendri Chinensis Cortex, Phellodendri Amurensis Cortex and Corydalis Decumbentis Rhizoma, with 99, 169, 50, 64 and 40 new compounds identified, respectively. Among these, 8, 14, 8, 7 and 12 berberines were confirmed by reference compounds. This strategy provides a new research paradigm for the rapid discovery and identification of different types of new compounds in complex samples.

Integration of High-Resolution LC-Q-TOF Mass Spectrometry and Multidimensional Chemical-Biological Analysis to Detect Nanomolar-Level Acetylcholinesterase Inhibitors from Different Parts of Zanthoxylum nitidum

Zanthoxyli radix is a popular tea among the elderly, and it is believed to have a positive effect on Alzheimer's disease. In this study, a highly effective three-step strategy was proposed for comprehensive analysis of the active components and biological functions of Zanthoxylum nitidum (ZN), including high-resolution LC-Q-TOF mass spectrometry (HRMS), multivariate statistical analysis for heterogeneity (MSAH), and experimental and virtual screening for bioactivity analysis (EVBA). A total of 117 compounds were identified from the root, stem, and leaf of ZN through HRMS. Bioactivity assays showed that the order of acetylcholinesterase (AChE) inhibitory activity from strong to weak was root > stem > leaf. Nitidine, chelerythrine, and sanguinarine were found to be the main differential components of root, stem, and leaf by OPLS-DA. The IC50 values of the three compounds are 0.81 ± 0.02, 0.14 ± 0.01, and 0.48 ± 0.01 μM respectively, indicating that they are potent and high-quality AChE inhibitors. Molecular docking showed that pi-pi T-shaped interactions and pi-lone pairs played important roles in AChE inhibition. This study not only explains the biological function of Zanthoxyli radix in alleviating Alzheimer's disease to some extent, but also lays the foundation for the development of stem and leaf of ZN.

Machine-learning-driven optical immunosensor based on microspheres-encoded signal transduction for the rapid and multiplexed detection of antibiotics in milk

Antibiotic residues are the most common contaminants in milk and other related dairy products. Simultaneous, convenient, and stable detection of antibiotic residues in foods is vital to secure public health. Herein, we proposed an optical immunosensor with easily-functionalized polystyrene nanoparticles differing in size and quantity, and bearing multiplex signal probes for the simultaneous detection of multiple antibiotics through a simple one-step signal conversion reaction. After the integration of the machine-learning-based transcoding analysis, this sensor is suitable for multiplexed detection of antibiotics in a broad linear range from pg/mL to ng/mL within 30 min, with an overall accuracy of >99 %. Compared to the conventional standard chemiluminescence immunoassays, this immunosensor is suitable for the accurate quantification of multiple antibiotics in milk, with improved accuracy, reduced costs, and simplified procedure. This ensures its applications in food safety monitoring when simultaneous detection of multiple hazardous substances in food matrices is needed.

Screening of Key Components for Melanogenesis Inhibition of Polygonum cuspidatum Extract Based on the Spectrum-Effect Relationship and Molecular Docking

Polygonum cuspidatum (PC) extract has been listed in the "Catalog of Used Cosmetic Ingredients (2021 Edition)", which can inhibit melanogenesis, thus exerting a whitening effect, and has been widely used in cosmetics. However, there are currently no quality standards for PC extract used in cosmetics, and the bioactive components associated with anti-melanogenesis remain unclear. In view of this, the present study was the first to investigate the spectrum-effect relationship between fingerprints of PC extract and melanogenesis inhibition. Ten batches of PC extract fingerprints were established by HPLC. Pearson's correlation analysis, gray correlation analysis (GRA) and orthogonal partial least squares regression analysis (OPLSR) were used to screen out resveratrol, emodin and physcion as the main whitening active ingredients using the inhibition of tyrosinase in B16F10 cells as the pharmacological index. Then, the melanogenesis inhibitory effects of the above three components were verified by tyrosinase inhibition and a melanin content assay in B16F10 cells. The interaction between small molecules and proteins was investigated by the molecular docking method, and it was confirmed by quantitative real-time PCR (qRT-PCR) that resveratrol, emodin and physcion significantly down-regulated the transcript levels of melanogenesis-related factors. In conclusion, this study established a general model combining HPLC fingerprinting and melanogenesis inhibition and also analyzed the spectrum-effect relationship of PC extract, which provided theoretical support for the quality control of PC extract in whitening cosmetics.

Pancreatic beta cell regenerative potential of Zanthoxylum chalybeum Engl. Aqueous stem bark extract

ETHNOPHARMACOLOGICAL RELEVANCE

Zanthoxylum chalybeum Engl. is endemic to Africa and has been used traditionally to treat diabetes mellitus. Moreover, its pharmacological efficacy has been confirmed experimentally using in vitro and in vivo models of diabetes. However, the effects of Z. chalybeum extracts and its major constituent compounds on beta cell and islet regeneration are not clear. Further, the mechanisms associated with observed antidiabetic effects at the beta cell level are not fully elucidated.

AIM OF THE STUDY

We determined the beta cell regenerative efficacy of Z. chalybeum aqueous stem bark extract, identified the chemical compounds in Z. chalybeum aqueous stem bark extracts and explored their putative mechanisms of action.

MATERIALS AND METHODS

Phytochemical profiling of the Z. chalybeum extract was achieved using ultra high-performance liquid chromatography hyphenated to high-resolution mass spectrometry. Thereafter, molecular interactions of the compounds with beta cell regeneration targets were evaluated via molecular docking. In vitro, effects of the extract on cell viability, proliferation, apoptosis and oxidative stress were investigated in RIN-5F beta cells exposed to palmitate or streptozotocin. In vivo, pancreas tissue sections from streptozotocin-induced diabetic male Wistar rats treated with Z. chalybeum extract were stained for insulin, glucagon, pancreatic duodenal homeobox protein 1 (Pdx-1) and Ki-67.

RESULTS

Based on ligand target and molecular docking interactions diosmin was identified as a dual specificity tyrosine-phosphorylation-regulated kinase 1A (Dyrk1A) inhibitor. In vitro, Z. chalybeum augmented cell viability and cell proliferation while in palmitate-pre-treated cells, the extract significantly increased cell activity after 72 h. In vivo, although morphometric analysis showed decreased islet and beta cell size and density, observation of increased Pdx-1 and Ki-67 immunoreactivity in extract-treated islets suggests that Z. chalybeum extract has mild beta cell regenerative potential mediated by increased cell proliferation.

CONCLUSIONS

Overall, the mitogenic effects observed in vitro, were not robust enough to elicit sufficient recovery of functional beta cell mass in our in vivo model, in the context of a sustained diabetic milieu. However, the identification of diosmin as a potential Dyrk1A inhibitor merits further inquiry into the attendant molecular interactions.

Research on the quality markers of antioxidant activity of Kai-Xin-San based on the spectrum-effect relationship

Background: Kai-Xin-San (KXS) is one of the classic famous traditional Chinese medicine prescriptions for amnesia, which has been applied for thousands of years. Modern pharmacological research has found that KXS has significant therapeutic efficacy on nervous system diseases, which is related to its antioxidant activity. However, the antioxidant material basis and quality markers (Q-makers) of KXS have not been studied. Objective: The objective of this study is to explore the Q-makers of antioxidant activity of KXS based on spectrum-effect relationship. Methods: Specifically, the metabolites in KXS extracts were identified by UPLC-Q-Exactive Orbitrap MS/MS. The fingerprint profile of KXS extracts were established by high-performance liquid chromatography (HPLC) and seven common peaks were identified. Meanwhile, 2, 2-diphenyl-1-picrylhydrazyl (DPPH) test was used to evaluate the free radical scavenging ability of KXS. The spectrum-effect relationship between its HPLC fingerprint and DPPH free radical scavenging activity was preliminarily examined by the Pearson correlation analysis, grey relation analysis (GRA), and orthogonal partial least squares discrimination analysis (OPLS-DA). Further, the antioxidant effect of KXS and its Q-makers were validated through human neuroblastoma (SH-SY5Y) cells experiment. Results: The results showed that 103 metabolites were identified from KXS, and the similarity values between HPLC fingerprint of twelve batches of KXS were greater than 0.900. At the same time, the results of Pearson correlation analysis showed that the peaks 8, 1, 14, 17, 18, 24, 16, 21, 15, 13, 6, 5, and 3 from KXS were positively correlated with the scavenging activity values of DPPH. Combined with the results of GRA and OPLS-DA, peaks 1, 3, 5 (Sibiricose A6), 6, 13 (Ginsenoside Rg1), 15, and 24 in the fingerprints were screen out as the potential Q-makers of KXS for antioxidant effect. Besides, the results of CCK-8 assay showed that KXS and its Q-makers remarkably reduced the oxidative damage of SH-SY5Y cells caused by H2O2. However, the antioxidant activity of KXS was decreased significantly after Q-makers were knocked out. Conclusion: In conclusion, the metabolites in KXS were successfully identified by UPLC-Q-Exactive Orbitrap MS/MS, and the Q-makers of KXS for antioxidant effect was analyzed based on the spectrum-effect relationship. These results are beneficial to clarify the antioxidant material basis of KXS and provide the quality control standards for new KXS products development.

Investigation of the Material Basis of Xiexin Tang to Alleviate Type 2 Diabetes Mellitus Based on Spectrum-Effect Analysis by UPLC-Q-TOF/MS

Xiexin Tang (XXT) is a classic prescription for treating diabetes in clinical practices for thousands of years in China, which has been also proved by a large number of modern pharmacological studies. However, due to its complex composition, the bioactive ingredients of XXT is still unclear. In present researches, spectrum-effect relationship analysis is widely used to explore the material basis of traditional medical herbs, so this method was adopted in this study. Firstly, the extract of XXT was separated and enriched into 5 fractions by macroporous adsorption resin. Then, UPLC-Q-TOF/MS method was used for qualitative identification of components in each eluting part, and efficacy of each fraction was assessed by the T2DM rat model. Based on grey relational analysis and pearson bivariate correlation analysis, it was found that the components such as berberine, gallic acid, catechin, epicatechin, acteoside, berberastine and 1-O-galloyl-β-D-glucose might be the main effective basis of XXT to improve T2DM.

A stepwise strategy integrating metabolomics and pseudotargeted spectrum–effect relationship to elucidate the potential hepatotoxic components in Polygonum multiflorum

Polygonummultiflorum (PM) Thunb., a typical Chinese herbal medicine with different therapeutic effect in raw and processed forms, has been used worldwide for thousands of years. However, hepatotoxicity caused by PM has raised considerable concern in recent decades. The exploration of toxic components in PM has been a great challenge for a long time. In this study, we developed a stepwise strategy integrating metabolomics and pseudotargeted spectrum–effect relationship to illuminate the potential hepatotoxic components in PM. First, 112 components were tentatively identified using ultraperformance liquid chromatography-quadrupole-time-of-flight-mass spectrometry (UPLC-Q-TOF-MS). Second, based on the theory of toxicity attenuation after processing, we combined the UPLC-Q-TOF-MS method and plant metabolomics to screen out the reduced differential components in PM between raw and processed PM. Third, the proposed pseudotargeted MS of 16 differential components was established and applied to 50 batches of PM for quantitative analysis. Fourth, the hepatocytotoxicity of 50 batches of PM was investigated on two hepatocytes, LO2 and HepG2. Last, three mathematical models, gray relational analysis, orthogonal partial least squares analysis, and back propagation artificial neural network, were established to further identify the key variables affecting hepatotoxicity in PM by combining quantitative spectral information with toxicity to hepatocytes of 50 batches of PM. The results suggested that 16 components may have different degrees of hepatotoxicity, which may lead to hepatotoxicity through synergistic effects. Three components (emodin dianthrones, emodin-8-O-β-D-glucopyranoside, PM 14-17) were screened to have significant hepatotoxicity and could be used as toxicity markers in PM as well as for further studies on the mechanism of toxicity. Above all, the study established an effective strategy to explore the hepatotoxic material basis in PM but also provides reference information for in-depth investigations on the hepatotoxicity of PM.